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中国农学通报 ›› 2023, Vol. 39 ›› Issue (24): 149-156.doi: 10.11924/j.issn.1000-6850.casb2022-0742

• 水产·渔业 • 上一篇    下一篇

小龙虾气候品质评价技术与应用

叶佩1(), 刘志雄2, 刘凯文1,3(), 刘可群2   

  1. 1 荆州农业气象试验站,湖北荆州 434000
    2 武汉区域气候中心,武汉 430074
    3 长江大学农学院,湖北荆州 434025
  • 收稿日期:2022-09-05 修回日期:2022-12-13 出版日期:2023-08-25 发布日期:2023-08-23
  • 通讯作者: 刘凯文,男,1985年出生,湖北黄冈人,高级工程师,博士研究生,博士,研究方向:水产养殖气象服务。通信地址:430074湖北省武汉市洪山区东湖东路3号 湖北省气象局,Tel:0716-15027136810,E-mail:kakahuohuo@163.com
  • 作者简介:

    叶佩,女,1994年出生,工程师,研究生,研究方向:农业气象与气候变化。通信地址:434000 湖北省荆州市荆州区九阳大道20号 荆州区气象局,Tel:0716-15927820104,E-mail:

  • 基金资助:
    湖北省气象局科技发展基金项目“小龙虾气候品质评价方法研究”(2020J07)

Technology and Application of Climate Quality Evaluation for Crayfish

YE Pei1(), LIU Zhixiong2, LIU Kaiwen1,3(), LIU Kequn2   

  1. 1 Jingzhou Agro-meteorology Experimental Station, Jingzhou, Hubei 434000
    2 Wuhan Regional Climate Center, Wuhan 430074
    3 School of Agriculture, Yangtze University, Jingzhou, Hubei 434025
  • Received:2022-09-05 Revised:2022-12-13 Online:2023-08-25 Published:2023-08-23

摘要:

通过开展分期投苗捕捞试验,测定不同养殖期小龙虾品质特征数据,结合1991—2020年荆州国家气象站逐日气象资料,采用方差分析、相关分析、逐步回归和主成分等方法,分析不同养殖期小龙虾品质特征差异,找出气候敏感性品质指标及关键气象因子,构建气候敏感性品质与关键气象因子关系模型及气候品质综合指数模型,确定小龙虾气候品质等级评价方法,并以荆州为例对历年不同投苗期小龙虾气候品质进行评价。结果表明:不同养殖期小龙虾常规营养成分、质构特性、氨基酸等品质因素存在差异性。氨基酸中缬氨酸、赖氨酸和质构特性中弹性、咀嚼性、回复性、黏性分别与小龙虾捕捞前1~35 d阴天数、1~30 d平均气温、1~35 d平均气温、1~20 d日较差、1~20 d阴天数、1~20 d雨日数相关性显著。以缬氨酸、赖氨酸、弹性、咀嚼性、回复性、黏性等品质因素构建小龙虾综合气候品质指数,并划分为“特优”、“优”、“良”、“一般”4个等级,相应阈值为>0.83、0.67~0.83、0.52~0.67、<0.52,荆州小龙虾气候品质随投苗时间序列呈现先差后优趋势,投苗期为4月5日—5月15日和9月5日—9月15日的小龙虾品质较优,投苗期为7月15日—8月5日的小龙虾品质较差。本研究建立的评价模型可作为小龙虾气候品质评价方法,用于开展小龙虾气候品质认证工作。

关键词: 小龙虾, 不同养殖期, 气候品质, 等级评价

Abstract:

Measuring the quality characteristics data of crayfish in different breeding periods by carrying out the staged seedling fishing experiment, and combining the daily meteorological data of Jingzhou National Meteorological Station from 1991 to 2020, the differences in the quality characteristics of crayfish in different breeding periods were analyzed by means of variance analysis, correlation analysis, stepwise regression and principal component methods, and the climate-sensitive quality indicators and the key meteorological factors were found out. The relationship model between climate-sensitive quality and key meteorological factors and a comprehensive index model of climate quality were established to determine the climate quality level of crayfish evaluation methods. Taking Jingzhou as an example, the climate quality of crayfish in different breeding periods was evaluated over the years. The results showed that there were differences in quality factors of crayfish in different breeding periods such as conventional nutrient components, texture characteristics, and amino acids. The valine and lysine in the amino acids and the elasticity, chewiness, resilience, and viscosity in the textural properties were significantly correlated with to the number of cloudy days of 1 to 35 days, the average temperature of 1 to 30 days, the average temperature of 1 to 35 days, the diurnal temperature difference of 1 to 20 days, the number of cloudy days of 1 to 20 days, and the number of rainy days of 1 to 20 days before the crayfish fishing. The comprehensive index characterization of crayfish climate quality was constructed based on quality factors such as valine, lysine, elasticity, chewiness, resilience, and stickiness, and was divided into four levels: extra excellent, excellent, good, and general, the corresponding thresholds of comprehensive index of climate quality were >0.83, 0.67-0.83, 0.52-0.67 and <0.52. The climate quality of crayfish in Jingzhou showed a trend of first poor and then good with the seedling time series. The quality of crayfish with the seedling period of April 5th-May 15th and September 5th-September 15th was better, and the quality of crayfish with the seedling period of July 15th-August 5th was poor. The evaluation model established in this study can be used as a crayfish climate quality evaluation method to carry out crayfish climate quality certification.

Key words: crayfish, different breeding stage, climate quality, level evaluation